For 40-year-old Mao Ya, the facial recognition camera that allows access
to her apartment house is simply a useful convenience.

“If I am carrying shopping bags in both hands, I just have to look ahead
and
the door swings open,” she said. “And my 5-year-old daughter can just look
up at the camera and get in. It’s good for kids because they often lose
their keys.”

But for the police, the cameras that replaced the residents’ old entry
cards
serve quite a different purpose.

Now they can see who’s coming and going, and by combining artificial
intelligence with a huge national bank of photos, the system in this pilot
project should enable police to identify what one police report, shared with
The Washington Post, called the “bad guys” who once might have slipped by.

The burger chain CaliBurger on Tuesday began testing a facial recognition
kiosk in its Pasadena, California, branch that can recognize customers who
set up loyalty accounts. The kiosk allows select customers to access their
accounts without any passcodes or card swipes and displays their order
histories once the facial scan confirms their identities. “Our goal for 2018
is to replace credit card swipes with face-based payments. Facial
recognition is part of our broader strategy,” CEO John Miller told the
Verge.

We recently reported how China continues to turn the online world into
the ultimate surveillance system, which hardly comes as a surprise, since
China has been relentlessly moving in this direction for years. What is
rather more surprising is that Chinese citizens are beginning to push back,
at least in certain areas. For example, The New York Times reports on an
"outcry" provoked by a division of the Alibaba behemoth when it assumed that
its users wouldn't worry too much if they were enrolled automatically in one
of China's commercially-run tracking systems.

Tech

Machine learning systems are very capable, but they aren’t exactly smart.
They lack common sense. Taking advantage of that fact, researchers have
created a wonderful attack on image recognition systems that uses specially
printed stickers that are so interesting to the AI that it completely fails
to see anything else.

Here, we present a novel image reconstruction method, in which the pixel
values of an image are optimized to make its DNN features similar to those
decoded from human brain activity at multiple layers. We found that the
generated images resembled the stimulus images (both natural images and
artificial shapes) and the subjective visual content during imagery.

Many great ideas in artificial intelligence languish in textbooks for
decades because we don’t have the computational power to apply them. That’s
what happened with neural networks, a technique inspired by our brains’
wiring that has recently succeeded in translating
languages and driving
cars. Now, another old idea—improving neural networks not through
teaching, but through evolution—is revealing its potential. Five new papers from
Uber in San Francisco, California, demonstrate the power of so-called
neuroevolution to play video games, solve mazes, and even make a simulated
robot walk.